Innovative approaches and tools play an important role in shaping design, characterization and optimization for the field of photonics. As a subset of machine learning that learns …
Deep neural networks (DNNs) are empirically derived systems that have transformed traditional research methods, and are driving scientific discovery. Artificial electromagnetic …
This article presents an overview of artificial neural network (ANN) techniques for a microwave computer-aided design (CAD). ANN-based techniques are becoming useful for …
Neural-network computational modules have recently gained recognition as an unconventional and useful tool for RF and microwave modeling and design. Neural …
JE Rayas-Sánchez - IEEE Transactions on Microwave Theory …, 2004 - ieeexplore.ieee.org
This paper reviews the current state-of-the-art in electromagnetic (EM)-based design and optimization of microwave circuits using artificial neural networks (ANNs). Measurement …
Microwave CAD has its roots in the 1960s [1]. Its practice saw the enrichment of circuit- based model libraries, advances in EM and circuit simulation accuracy, and the refinement …
Axial bearing capacity of piles is the most important parameter in pile foundation design. In this paper, artificial neural network (ANN) and random forest (RF) algorithms were utilized to …
H Kabir, Y Wang, M Yu… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
In this paper, systematic neural network modeling techniques are presented for microwave modeling and design using the concept of inverse modeling where the inputs to the inverse …
Modeling and computer-aided design (CAD) techniques are essential for microwave design, especially with the drive towards first-pass design success. We have described neural …